Similarity Search Techniques in Exploratory Search: A Review

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The past decade has seen a dramatic increase in the amount of data captured and made available to users for research. This increase amplifies the difficulties users' face in finding the data most relevant to their information needs. The document similarity search is one of the most important topics in the field of information science, especially due to the popularity of the internet applications that deal with unstructured data sources such as World Wide Web. Efficiency of similarity search has become one of the most important issues. A typical example of similarity search is in multimedia databases that manage objects without structure, i.e. images, fingerprints or audio clips. Here similarity search is involved in retrieving the most similar fingerprint to a given one. Another example is in text retrieval which is present in many systems, from simple text editors (finding words similar to a given one to correct edition errors) to big search engines (retrieving relevant documents for a given query). This study explores the use of similarity search for text data in the form of a brief review using the interface provided as a service after content-based searches has been performed. The findings will give us ideas as to how to incorporate similarity searches within others search engine architecture.

Original languageEnglish
Title of host publicationProceedings of TENCON 2018 - 2018 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2193-2198
Number of pages6
ISBN (Electronic)9781538654576
DOIs
Publication statusPublished - 22 Feb 2019
Event2018 IEEE Region 10 Conference, TENCON 2018 - Jeju, Korea, Republic of
Duration: 28 Oct 201831 Oct 2018

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume2018-October
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2018 IEEE Region 10 Conference, TENCON 2018
CountryKorea, Republic of
CityJeju
Period28/10/1831/10/18

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Mahdi, M., Ahmad, A. R., & Ismail, R. (2019). Similarity Search Techniques in Exploratory Search: A Review. In Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference (pp. 2193-2198). [8650257] (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2018-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2018.8650257